Self-organizing 3D human neural tissue derived from induced pluripotent stem cells recapitulate Alzheimer's disease phenotypes

  • Waseem K. Raja
  • , Alison E. Mungenast
  • , Yuan Ta Lin
  • , Tak Ko
  • , Fatema Abdurrob
  • , Jinsoo Seo
  • , Li Huei Tsai

Research output: Contribution to journalArticlepeer-review

438 Scopus citations

Abstract

The dismal success rate of clinical trials for Alzheimer's disease (AD) motivates us to develop model systems of AD pathology that have higher predictive validity. The advent of induced pluripotent stem cells (iPSCs) allows us to model pathology and study disease mechanisms directly in human neural cells from healthy individual as well as AD patients. However, two-dimensional culture systems do not recapitulate the complexity of neural tissue, and phenotypes such as extracellular protein aggregation are difficult to observe.We report brain organoids that use pluripotent stem cells derived from AD patients and recapitulate AD-like pathologies such as amyloid aggregation, hyperphosphorylated tau protein, and endosome abnormalities. These pathologies are observed in an age-dependent manner in organoids derived frommultiple familial AD (fAD) patients harboringamyloid precursor protein (APP) duplication or presenilin1 (PSEN1)mutation, compared to controls. The incidence of AD pathology was consistent amongst several fAD lines, which carried differentmutations. Although these are complex assemblies of neural tissue, they are also highly amenable to experimental manipulation.We find that treatment of patient-derived organoids with β-And γ-secretase inhibitors significantly reduces amyloid and tau pathology. Moreover, these results show the potential of this model system to greatly increase the translatability of pre-clinical drug discovery in AD.

Original languageEnglish
Article numbere0161969
JournalPLoS ONE
Volume11
Issue number9
DOIs
StatePublished - Sep 2016

Bibliographical note

Publisher Copyright:
© 2016 Raja et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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